Fastpose

​ Fastpose is an open source library that can perform a 2D/3D pose estimation in real time on a CPU.

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Get Started

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Install the dependencies:

# create the environment
conda create -n fastpose python=3.6
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# The both following packages are non-gpu apis
conda install -c conda-forge tensorflow
conda install pytorch torchvision -c pytorch
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# older version of opencv can lead to error (version 3.4.2)
conda install opencv
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conda install matplotlib
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conda install requests

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Download the Project:

Download the project source code and the parameter’s archive that embeds the exported graph in .pb (protograph) as well as the training tensorflow checkpoints. When the download is completed, unzip the parameters in the project root’s folder. ​ By default, the 2D inference is made with the tiny version, the medium version is not fully converged and its just a bit more accurate than the tiny one while decreasing the speed by more than a factor 2. This is why, without any extra work, the selected models do not have to be modified. ​

Activate the environment

source activate fastpose

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Run Fastpose

2D demo: Launch the pose estimator by running demo_2d.py in the root folder of the project:

python demo_2d.py [webcam | path_to_video_file] max_person_threshold

​ 2D/3D demo: Fastpose also provides a tiny backend working on the loopback to allow better compatibility with other programming languages. To use fastpose in localhost, start backend.py in the root folder of the project: ​

python backend.py port_number max_person_threshold

​ frontend_2d.py sends the image to the backend and displays the visualization while frontend_3d.html is a 3D visualization made in html (D3) that can display the 3D pose estimation performed over the video stream sent by frontend_2d.py. ​ From an external server: If you need to run the backend script on an external server this unix command redirects the annotation stream into your localhost ip on the port_frontend : ​

ssh -i ~/.ssh/server_private_key -f user@ip -L port_frontend:localhost:port_backend -N

​ ​ For more more information, check out this blog post from the author.